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@cli.command() @click.option('-d', '--directory', default='./', type=click.Path(), required=True) def examples(directory): source_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'examples') try: shutil.copytree(source_dir, os.path.join(directory, 'examples')) except OSError as e: if (e.errno == errno.EEXIST): print_('Folder examples is exists.')
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generate example strategies to target folder .
train
false
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def htons(integer): return ntohs(integer)
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convert integer in n from host-byte order to network-byte order .
train
false
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def callInThreadPool(fun, *args, **kwargs): if isInThreadPool(): fun(*args, **kwargs) else: reactor.callFromThread(reactor.callInThread, fun, *args, **kwargs)
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calls fun in the reactors thread pool .
train
false
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def p_init_declarator_list_2(t): pass
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init_declarator_list : init_declarator_list comma init_declarator .
train
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def merge_mean_color(graph, src, dst): graph.node[dst]['total color'] += graph.node[src]['total color'] graph.node[dst]['pixel count'] += graph.node[src]['pixel count'] graph.node[dst]['mean color'] = (graph.node[dst]['total color'] / graph.node[dst]['pixel count'])
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callback called before merging two nodes of a mean color distance graph .
train
false
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def random_organism(): genome = random_genome() return Organism(genome, test_fitness)
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generate a random organism .
train
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def basestation(): return s3_rest_controller()
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restful crud controller for base stations .
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def observe_lr(optimizer_name='main', observation_key='lr'): return observe_value(observation_key, (lambda trainer: trainer.updater.get_optimizer(optimizer_name).lr))
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returns a trainer extension to record the learning rate .
train
false
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def user_confirm(prompt, default=False): if default: prompt_default = '[Y/n]' else: prompt_default = '[y/N]' answer = input(('%s %s ' % (prompt, prompt_default))) if (answer == ''): return default else: return (answer.lower() in ('yes', 'y'))
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yes/no question dialog with user .
train
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def send_email_for_monthly_fee_payment(email, event_name, date, amount, payment_url): send_email(to=email, action=MONTHLY_PAYMENT_EMAIL, subject=MAILS[MONTHLY_PAYMENT_EMAIL]['subject'].format(event_name=event_name, date=date), html=MAILS[MONTHLY_PAYMENT_EMAIL]['message'].format(event_name=event_name, date=date, payment_url=payment_url, amount=amount, app_name=get_settings()['app_name']))
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send email every month with invoice to pay service fee .
train
false
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def lighten(color, percent): return adjust(color, 2, percent)
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lighten a color by increasing its lightness by percent .
train
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def _find_channels(ch_names, ch_type='EOG'): substrings = (ch_type,) substrings = [s.upper() for s in substrings] if (ch_type == 'EOG'): substrings = ('EOG', 'EYE') eog_idx = [idx for (idx, ch) in enumerate(ch_names) if any(((substring in ch.upper()) for substring in substrings))] return eog_idx
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find eog channel .
train
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def test_sobel_v_vertical(): (i, j) = np.mgrid[(-5):6, (-5):6] image = (j >= 0).astype(float) result = filters.sobel_v(image) j[(np.abs(i) == 5)] = 10000 assert np.all((result[(j == 0)] == 1)) assert np.all((result[(np.abs(j) > 1)] == 0))
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vertical sobel on an edge should be a vertical line .
train
false
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def expand_paths(inputs): seen = {} for dirname in inputs: dirname = normalize_path(dirname) if (dirname in seen): continue seen[dirname] = 1 if (not os.path.isdir(dirname)): continue files = os.listdir(dirname) (yield (dirname, files)) for name in files: if (not name.endswith('.pth')): continue if (name in ('easy-install.pth', 'setuptools.pth')): continue f = open(os.path.join(dirname, name)) lines = list(yield_lines(f)) f.close() for line in lines: if (not line.startswith('import')): line = normalize_path(line.rstrip()) if (line not in seen): seen[line] = 1 if (not os.path.isdir(line)): continue (yield (line, os.listdir(line)))
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yield sys .
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def batch_get_value(xs): if xs: return get_session().run(xs) else: return []
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returns the value of more than one tensor variable .
train
false
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@transaction.non_atomic_requests @ensure_csrf_cookie @cache_control(no_cache=True, no_store=True, must_revalidate=True) @require_global_staff @require_POST def start_certificate_generation(request, course_id): course_key = CourseKey.from_string(course_id) task = lms.djangoapps.instructor_task.api.generate_certificates_for_students(request, course_key) message = _('Certificate generation task for all students of this course has been started. You can view the status of the generation task in the "Pending Tasks" section.') response_payload = {'message': message, 'task_id': task.task_id} return JsonResponse(response_payload)
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start generating certificates for all students enrolled in given course .
train
false
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def get_stories(f, only_supporting=False, max_length=None): data = parse_stories(f.readlines(), only_supporting=only_supporting) flatten = (lambda data: reduce((lambda x, y: (x + y)), data)) data = [(flatten(story), q, answer) for (story, q, answer) in data if ((not max_length) or (len(flatten(story)) < max_length))] return data
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given a file name .
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false
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def verify_signature(secret, parts): if (signature(secret, parts[:(-1)]) == parts[(-1)]): return True else: return False
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check the signature in the message .
train
false
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def ordinal(value): try: value = int(value) except (TypeError, ValueError): return value t = ('th', 'st', 'nd', 'rd', 'th', 'th', 'th', 'th', 'th', 'th') if ((value % 100) in (11, 12, 13)): return (u'%d%s' % (value, t[0])) return (u'%d%s' % (value, t[(value % 10)]))
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converts an integer to its ordinal as a string .
train
false
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def pnt_func(f): return double_output(f, [c_void_p, c_int])
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for accessing point information .
train
false
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def cms_documentation(r, default_page, default_url): row = r.record if (not row): name = r.get_vars.get('name', default_page) table = r.resource.table query = ((table.name == name) & (table.deleted != True)) row = current.db(query).select(table.id, table.title, table.body, limitby=(0, 1)).first() if (not row): if (name != default_page): r.error(404, current.T('Page not found'), next=URL(args=current.request.args, vars={})) else: from s3 import s3_redirect_default s3_redirect_default(default_url) from s3 import S3XMLContents return {'bypass': True, 'output': {'title': row.title, 'contents': S3XMLContents(row.body)}}
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render an online documentation page .
train
false
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def git_line(*items): return (' '.join(items) + '\n')
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formats items into a space sepreated line .
train
false
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def sanitizeStr(value): return getUnicode(value).replace('\n', ' ').replace('\r', '')
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sanitizes string value in respect to newline and line-feed characters .
train
false
15,067
@task def sharejs(ctx, host=None, port=None, db_url=None, cors_allow_origin=None): if host: os.environ['SHAREJS_SERVER_HOST'] = host if port: os.environ['SHAREJS_SERVER_PORT'] = port if db_url: os.environ['SHAREJS_DB_URL'] = db_url if cors_allow_origin: os.environ['SHAREJS_CORS_ALLOW_ORIGIN'] = cors_allow_origin if settings.SENTRY_DSN: os.environ['SHAREJS_SENTRY_DSN'] = settings.SENTRY_DSN share_server = os.path.join(settings.ADDON_PATH, 'wiki', 'shareServer.js') ctx.run('node {0}'.format(share_server))
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start a local sharejs server .
train
false
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def assign_role(course_id, user, rolename): (role, __) = Role.objects.get_or_create(course_id=course_id, name=rolename) user.roles.add(role)
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assign forum role rolename to user .
train
false
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def perform_m_search(local_ip): search_target = 'urn:schemas-upnp-org:device:InternetGatewayDevice:1' ssdp_request = ''.join(['M-SEARCH * HTTP/1.1\r\n', 'HOST: 239.255.255.250:1900\r\n', 'MAN: "ssdp:discover"\r\n', 'MX: 2\r\n', 'ST: {0}\r\n'.format(search_target), '\r\n']) sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) sock.bind((local_ip, 10000)) sock.sendto(ssdp_request, ('239.255.255.250', 1900)) if (local_ip == '127.0.0.1'): sock.settimeout(1) else: sock.settimeout(5) try: return sock.recv(2048) except socket.error: raise UpnpError('No reply from IGD using {} as IP'.format(local_ip)) finally: sock.close()
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broadcast a udp ssdp m-search packet and return response .
train
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def set_system_date(newdate, utc_offset=None): fmts = ['%Y-%m-%d', '%m-%d-%Y', '%m-%d-%y', '%m/%d/%Y', '%m/%d/%y', '%Y/%m/%d'] dt_obj = _try_parse_datetime(newdate, fmts) if (dt_obj is None): raise SaltInvocationError('Invalid date format') return set_system_date_time(years=dt_obj.year, months=dt_obj.month, days=dt_obj.day, utc_offset=utc_offset)
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set the windows system date .
train
true
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def is_builtin_class_method(obj, attr_name): classes = [c for c in inspect.getmro(obj) if (attr_name in c.__dict__)] cls = (classes[0] if classes else object) if (not hasattr(builtins, safe_getattr(cls, '__name__', ''))): return False return (getattr(builtins, safe_getattr(cls, '__name__', '')) is cls)
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if attr_name is implemented at builtin class .
train
false
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def s_binary(value, name=None): parsed = value parsed = parsed.replace(' ', '') parsed = parsed.replace(' DCTB ', '') parsed = parsed.replace('\r', '') parsed = parsed.replace('\n', '') parsed = parsed.replace(',', '') parsed = parsed.replace('0x', '') parsed = parsed.replace('\\x', '') value = '' while parsed: pair = parsed[:2] parsed = parsed[2:] value += chr(int(pair, 16)) static = primitives.static(value, name) blocks.CURRENT.push(static)
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parse a variable format binary string into a static value and push it onto the current block stack .
train
false
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@pytest.mark.skipif('not HAS_BEAUTIFUL_SOUP') def test_no_names(): table_in = ['<table>', '<tr><td>1</td></tr>', '<tr><td>2</td></tr>', '</table>'] dat = Table.read(table_in, format='ascii.html') assert (dat.colnames == ['col1']) assert (len(dat) == 2) dat = Table.read(table_in, format='ascii.html', names=['a']) assert (dat.colnames == ['a']) assert (len(dat) == 2)
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test reading a table witn no column header .
train
false
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def get_path_style(path, fill=True): style = {} style['alpha'] = path.get_alpha() if (style['alpha'] is None): style['alpha'] = 1 style['edgecolor'] = color_to_hex(path.get_edgecolor()) if fill: style['facecolor'] = color_to_hex(path.get_facecolor()) else: style['facecolor'] = 'none' style['edgewidth'] = path.get_linewidth() style['dasharray'] = get_dasharray(path) style['zorder'] = path.get_zorder() return style
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get the style dictionary for matplotlib path objects .
train
true
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def dllFromDll(dllid): if (dllid == None): return None elif (type('') == type(dllid)): return win32ui.LoadLibrary(dllid) else: try: dllid.GetFileName() except AttributeError: raise TypeError('DLL parameter must be None, a filename or a dll object') return dllid
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given a dll .
train
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def is_available_extension(name, user=None, host=None, port=None, maintenance_db=None, password=None, runas=None): exts = available_extensions(user=user, host=host, port=port, maintenance_db=maintenance_db, password=password, runas=runas) if (name.lower() in [a.lower() for a in exts]): return True return False
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test if a specific extension is available cli example: .
train
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def list_tables(dataset_name, project=None): bigquery_client = bigquery.Client(project=project) dataset = bigquery_client.dataset(dataset_name) if (not dataset.exists()): print 'Dataset {} does not exist.'.format(dataset_name) return for table in dataset.list_tables(): print table.name
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lists all of the tables in a given dataset .
train
false
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def receive_message(sock, operation, request_id, max_message_size=MAX_MESSAGE_SIZE): header = _receive_data_on_socket(sock, 16) length = _UNPACK_INT(header[:4])[0] actual_op = _UNPACK_INT(header[12:])[0] if (operation != actual_op): raise ProtocolError(('Got opcode %r but expected %r' % (actual_op, operation))) if (request_id is not None): response_id = _UNPACK_INT(header[8:12])[0] if (request_id != response_id): raise ProtocolError(('Got response id %r but expected %r' % (response_id, request_id))) if (length <= 16): raise ProtocolError(('Message length (%r) not longer than standard message header size (16)' % (length,))) if (length > max_message_size): raise ProtocolError(('Message length (%r) is larger than server max message size (%r)' % (length, max_message_size))) return _receive_data_on_socket(sock, (length - 16))
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run a label request on an image received from twilio .
train
true
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def compare_forwards(f1, f2): assert_allclose(f1['sol']['data'], f2['sol']['data']) assert_equal(f1['sol']['ncol'], f2['sol']['ncol']) assert_allclose(f1['source_nn'], f2['source_nn']) if (f1['sol_grad'] is not None): assert_true((f2['sol_grad'] is not None)) assert_allclose(f1['sol_grad']['data'], f2['sol_grad']['data']) assert_equal(f1['sol_grad']['ncol'], f2['sol_grad']['ncol']) else: assert_true((f2['sol_grad'] is None)) assert_equal(f1['source_ori'], f2['source_ori']) assert_equal(f1['surf_ori'], f2['surf_ori'])
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helper to compare two potentially converted forward solutions .
train
false
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def compute_P_from_fundamental(F): e = compute_epipole(F.T) Te = skew(e) return vstack((dot(Te, F.T).T, e)).T
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computes the second camera matrix from a fundamental matrix .
train
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def autoTrack(clip, pattern, tt=None, fps=None, radius=20, xy0=None): if (not autotracking_possible): raise IOError('Sorry, autotrack requires OpenCV for the moment. Install OpenCV (aka cv2) to use it.') if (not xy0): xy0 = findAround(clip.get_frame(tt[0]), pattern) if (tt is None): tt = np.arange(0, clip.duration, (1.0 / fps)) xys = [xy0] for t in tt[1:]: xys.append(findAround(clip.get_frame(t), pattern, xy=xys[(-1)], r=radius)) (xx, yy) = zip(*xys) return Trajectory(tt, xx, yy)
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tracks a given pattern in a video clip .
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@image_comparison(baseline_images=[u'bbox_inches_tight_raster'], remove_text=True, savefig_kwarg={u'bbox_inches': u'tight'}) def test_bbox_inches_tight_raster(): fig = plt.figure() ax = fig.add_subplot(111) ax.plot([1.0, 2.0], rasterized=True)
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test rasterization with tight_layout .
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@hook.command() @hook.command('tv_prev') def tv_last(text, bot=None): api_key = bot.config.get('api_keys', {}).get('tvdb', None) if (api_key is None): return 'error: no api key set' episodes = get_episodes_for_series(text, api_key) if episodes['error']: return episodes['error'] series_name = episodes['name'] ended = episodes['ended'] episodes = episodes['episodes'] prev_ep = None today = datetime.date.today() for episode in reversed(episodes): ep_info = get_episode_info(episode) if (ep_info is None): continue (first_aired, air_date, episode_desc) = ep_info if (air_date < today): prev_ep = '{} ({})'.format(first_aired, episode_desc) break if (not prev_ep): return 'There are no previously aired episodes for {}.'.format(series_name) if ended: return '{} ended. The last episode aired {}.'.format(series_name, prev_ep) return 'The last episode of {} aired {}.'.format(series_name, prev_ep)
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tv_last <series> -- gets the most recently aired episode of <series> .
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def iscode(object): return isinstance(object, types.CodeType)
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return true if the object is a code object .
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def test_url_incorrect_case_file_index(script, data): result = script.pip('install', '--index-url', data.find_links3, 'dinner', expect_stderr=True) egg_folder = ((script.site_packages / 'Dinner-1.0-py%s.egg-info') % pyversion) assert (egg_folder not in result.files_created), str(result) egg_folder = ((script.site_packages / 'Dinner-2.0-py%s.egg-info') % pyversion) assert (egg_folder in result.files_created), str(result)
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same as test_url_req_case_mismatch_file_index .
train
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def query_helper(query, add=None, remove=None): add = string_to_dict(add) remove = string_to_list(remove) params = query.copy() return get_query_string(params, add, remove)
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helper function for use within views .
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false
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def do_collectstatic(): try: build.make_collectstatic() return True except (OSError, SystemError) as ex: LOG.error(("Failed to collect the static files. Please fix any problem and run `%s --collectstatic'\n%s" % (PROG_NAME, ex))) return False
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collects the static files .
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def get_archive_content(filename): archive = get_archive(filename) stack.append((filename, archive)) output = [] get_content(archive, recursive=True, brief=True, output=output) do_cleanup() return output
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get a list of the content of archive filename .
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@public def factor_list(f, *gens, **args): return _generic_factor_list(f, gens, args, method='factor')
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compute a list of irreducible factors of f .
train
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def find_cached_job(jid): serial = salt.payload.Serial(__opts__) proc_dir = os.path.join(__opts__['cachedir'], 'minion_jobs') job_dir = os.path.join(proc_dir, str(jid)) if (not os.path.isdir(job_dir)): if (not __opts__.get('cache_jobs')): return 'Local jobs cache directory not found; you may need to enable cache_jobs on this minion' else: return 'Local jobs cache directory {0} not found'.format(job_dir) path = os.path.join(job_dir, 'return.p') with salt.utils.fopen(path, 'rb') as fp_: buf = fp_.read() fp_.close() if buf: try: data = serial.loads(buf) except NameError: return else: return if (not isinstance(data, dict)): return return data
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return the data for a specific cached job id .
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def lod_to_dod(_list, indexkey): results = {} for item in _list: results[item[indexkey]] = item return results
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things like get_distros() returns a list of a dictionaries convert this to a dict of dicts keyed off of an arbitrary field ex: [ { "a" : 2 } .
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def replace_leaf(arg, leaves, new_leaves, op, neg): for (idx, x) in enumerate(leaves): if (x[0] == arg): x[1][0] ^= neg x[1][1] = op(arg) leaves.pop(idx) new_leaves.append(x) return True return False
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attempt to replace a leaf of a multiplication tree .
train
false
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def get_event_source_mapping_ids(EventSourceArn, FunctionName, region=None, key=None, keyid=None, profile=None): conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) try: mappings = [] for maps in salt.utils.boto3.paged_call(conn.list_event_source_mappings, EventSourceArn=EventSourceArn, FunctionName=FunctionName): mappings.extend([mapping['UUID'] for mapping in maps['EventSourceMappings']]) return mappings except ClientError as e: return {'error': salt.utils.boto3.get_error(e)}
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given an event source and function name .
train
false
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@validation_task def validate_file(file_id, hash_, is_webextension=False, **kw): file_ = File.objects.get(pk=file_id) try: return file_.validation.validation except FileValidation.DoesNotExist: listed = (file_.version.channel == amo.RELEASE_CHANNEL_LISTED) if is_webextension: return run_addons_linter(file_.current_file_path, listed=listed) return run_validator(file_.current_file_path, listed=listed)
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validate if requirements_all .
train
false
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def test_getattr_exceptions(): class AttributeTest(object, ): def __getattr__(self, name): raise AttributeError('catch me') x = AttributeTest() try: y = x.throws except AttributeError as ex: AreEqual(ex.args, ('catch me',)) else: Fail('should have thrown')
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verify the original exception propagates out .
train
false
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def readmission(aFileName): print ('\nReading mission from file: %s' % aFileName) cmds = vehicle.commands missionlist = [] with open(aFileName) as f: for (i, line) in enumerate(f): if (i == 0): if (not line.startswith('QGC WPL 110')): raise Exception('File is not supported WP version') else: linearray = line.split(' DCTB ') ln_index = int(linearray[0]) ln_currentwp = int(linearray[1]) ln_frame = int(linearray[2]) ln_command = int(linearray[3]) ln_param1 = float(linearray[4]) ln_param2 = float(linearray[5]) ln_param3 = float(linearray[6]) ln_param4 = float(linearray[7]) ln_param5 = float(linearray[8]) ln_param6 = float(linearray[9]) ln_param7 = float(linearray[10]) ln_autocontinue = int(linearray[11].strip()) cmd = Command(0, 0, 0, ln_frame, ln_command, ln_currentwp, ln_autocontinue, ln_param1, ln_param2, ln_param3, ln_param4, ln_param5, ln_param6, ln_param7) missionlist.append(cmd) return missionlist
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load a mission from a file into a list .
train
true
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def test_softmax_generality(): nvis = 1 num_classes = 2 model = MLP(layers=[Softmax(num_classes, 's', irange=0.1)], nvis=nvis) Z = T.matrix() Y_hat = T.nnet.softmax(Z) Y = T.matrix() model.layers[(-1)].cost(Y=Y, Y_hat=Y_hat)
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tests that the softmax layer can score outputs it did not create .
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@csrf_exempt def spell_check(request): try: if (not enchant): raise RuntimeError('install pyenchant for spellchecker functionality') raw = force_text(request.body) input = json.loads(raw) id = input['id'] method = input['method'] params = input['params'] lang = params[0] arg = params[1] if (not enchant.dict_exists(str(lang))): raise RuntimeError('dictionary not found for language {!r}'.format(lang)) checker = enchant.Dict(str(lang)) if (method == 'checkWords'): result = [word for word in arg if (word and (not checker.check(word)))] elif (method == 'getSuggestions'): result = checker.suggest(arg) else: raise RuntimeError('Unknown spellcheck method: {!r}'.format(method)) output = {'id': id, 'result': result, 'error': None} except Exception: logging.exception('Error running spellchecker') return HttpResponse(_('Error running spellchecker')) return HttpResponse(json.dumps(output), content_type='application/json')
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returns a httpresponse that implements the tinymce spellchecker protocol .
train
true
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def exit_standby(name, instance_ids, should_decrement_desired_capacity=False, region=None, key=None, keyid=None, profile=None): conn = _get_conn_autoscaling_boto3(region=region, key=key, keyid=keyid, profile=profile) try: response = conn.exit_standby(InstanceIds=instance_ids, AutoScalingGroupName=name) except ClientError as e: err = salt.utils.boto3.get_error(e) if (e.response.get('Error', {}).get('Code') == 'ResourceNotFoundException'): return {'exists': False} return {'error': err} return all(((activity['StatusCode'] != 'Failed') for activity in response['Activities']))
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exit desired instances from standby mode .
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def get_absolute_url(path): if is_absolute_url(path): return path site = sites.get_current() return build_url(path, scheme=site.scheme, domain=site.domain)
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generate an absolute url for a resource on the test server .
train
false
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def _default_course_mode(course_id): course_modes = CourseMode.modes_for_course(CourseKey.from_string(course_id)) available_modes = [m.slug for m in course_modes] if (CourseMode.DEFAULT_MODE_SLUG in available_modes): return CourseMode.DEFAULT_MODE_SLUG elif ('audit' in available_modes): return 'audit' elif ('honor' in available_modes): return 'honor' return CourseMode.DEFAULT_MODE_SLUG
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return the default enrollment for a course .
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def get_parsed_option(command_opts, opt_key, default=None): command_opt_value = getattr(command_opts, opt_key, default) if command_opt_value: command_opt_value = listfy(command_opt_value) return command_opt_value
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extract user command option and parse it .
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def on_agent(path, context): if (path == ''): path = '/' (folder, search_path) = get_folder_and_search_path(path, '/') folders = context.listFiles(folder) return [s.replace(' ', '\\ ') for s in get_suggestions(folder, search_path, map((lambda f: str(f)), folders), '/', True)]
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provides path completion .
train
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def compute_features(net, im): if config.FLAG_CPU_MODE: net.blobs['data'].reshape(*im.shape) net.blobs['data'].data[...] = im net.forward() fc7 = net.blobs['fc7'].data else: fc7 = numpy.array(lasagne.layers.get_output(net['fc7'], im, deterministic=True).eval()) return fc7
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compute fc7 features for im .
train
false
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def line_graph(G, create_using=None): if G.is_directed(): L = _lg_directed(G, create_using=create_using) else: L = _lg_undirected(G, selfloops=False, create_using=create_using) return L
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returns the line graph of the graph or digraph g .
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def _write_file_prefix(f, interpreter): if interpreter: shebang = (('#!' + interpreter.encode(shebang_encoding)) + '\n') f.write(shebang)
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write a shebang line .
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@csrf.exempt @api_experimental.route('/dags/<string:dag_id>/dag_runs', methods=['POST']) @requires_authentication def trigger_dag(dag_id): data = request.get_json(force=True) run_id = None if ('run_id' in data): run_id = data['run_id'] conf = None if ('conf' in data): conf = data['conf'] execution_date = None if ('execution_date' in data): execution_date = data['execution_date'] try: execution_date = datetime.strptime(execution_date, '%Y-%m-%dT%H:%M:%S') except ValueError: error_message = 'Given execution date, {}, could not be identified as a date. Example date format: 2015-11-16T14:34:15'.format(execution_date) _log.info(error_message) response = jsonify({'error': error_message}) response.status_code = 400 return response try: dr = trigger.trigger_dag(dag_id, run_id, conf, execution_date) except AirflowException as err: _log.error(err) response = jsonify(error='{}'.format(err)) response.status_code = 404 return response if getattr(g, 'user', None): _log.info('User {} created {}'.format(g.user, dr)) response = jsonify(message='Created {}'.format(dr)) return response
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creates a dag run for the specified dag .
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def getevents(clsid): clsid = str(pywintypes.IID(clsid)) klass = gencache.GetClassForCLSID(clsid) try: return klass.default_source except AttributeError: try: return gencache.GetClassForCLSID(klass.coclass_clsid).default_source except AttributeError: return None
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determine the default outgoing interface for a class .
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@intercept_errors(UserAPIInternalError, ignore_errors=[UserAPIRequestError]) def get_user_preference(requesting_user, preference_key, username=None): existing_user = _get_authorized_user(requesting_user, username, allow_staff=True) return UserPreference.get_value(existing_user, preference_key)
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returns the value of the user preference with the specified key .
train
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def map_process(path, wp, fen, used_flightmodes, options): from mavflightview import mavflightview_show mavflightview_show(path, wp, fen, used_flightmodes, options)
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process for displaying a graph .
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def add_user_to_cohort(cohort, username_or_email): user = get_user_by_username_or_email(username_or_email) membership = CohortMembership(course_user_group=cohort, user=user) membership.save() tracker.emit('edx.cohort.user_add_requested', {'user_id': user.id, 'cohort_id': cohort.id, 'cohort_name': cohort.name, 'previous_cohort_id': membership.previous_cohort_id, 'previous_cohort_name': membership.previous_cohort_name}) return (user, membership.previous_cohort_name)
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look up the given user .
train
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def json_synonym(name): def getter(self): return json.loads(getattr(self, name), decode_datetime=True) def setter(self, entry): setattr(self, name, unicode(json.dumps(entry, encode_datetime=True))) return synonym(name, descriptor=property(getter, setter))
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use json to serialize python objects for db storage .
train
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def setup_switch(device_id, name, insteonhub, hass, add_devices_callback): if (device_id in _CONFIGURING): request_id = _CONFIGURING.pop(device_id) configurator = get_component('configurator') configurator.request_done(request_id) _LOGGER.info('Device configuration done!') conf_switch = config_from_file(hass.config.path(INSTEON_LOCAL_SWITCH_CONF)) if (device_id not in conf_switch): conf_switch[device_id] = name if (not config_from_file(hass.config.path(INSTEON_LOCAL_SWITCH_CONF), conf_switch)): _LOGGER.error('Failed to save configuration file') device = insteonhub.switch(device_id) add_devices_callback([InsteonLocalSwitchDevice(device, name)])
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set up the switch .
train
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def verify_tunnel_range(tunnel_range, tunnel_type): mappings = {p_const.TYPE_GRE: is_valid_gre_id, p_const.TYPE_VXLAN: is_valid_vxlan_vni, p_const.TYPE_GENEVE: is_valid_geneve_vni} if (tunnel_type in mappings): for ident in tunnel_range: if (not mappings[tunnel_type](ident)): raise exceptions.NetworkTunnelRangeError(tunnel_range=tunnel_range, error=(_('%(id)s is not a valid %(type)s identifier') % {'id': ident, 'type': tunnel_type})) if (tunnel_range[1] < tunnel_range[0]): raise exceptions.NetworkTunnelRangeError(tunnel_range=tunnel_range, error=_('End of tunnel range is less than start of tunnel range'))
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raise an exception for invalid tunnel range or malformed range .
train
false
15,135
def formatted_response(response, fields, labels, iterable=None): output_format = validated_parameter(request.args, 'format', values=['json', 'json_lines', 'csv'], default='json') header_type = validated_parameter(request.args, 'header', values=['names', 'labels', 'none'], default='labels') if (header_type == 'names'): header = fields elif (header_type == 'labels'): header = labels else: header = None iterable = (iterable or response) if (output_format == 'json'): return jsonify(response) elif (output_format == 'json_lines'): return Response(JSONLinesGenerator(iterable), mimetype='application/x-json-lines') elif (output_format == 'csv'): generator = csv_generator(iterable, fields, include_header=bool(header), header=header) headers = {'Content-Disposition': 'attachment; filename="facts.csv"'} return Response(generator, mimetype='text/csv', headers=headers)
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wraps request which returns response that can be formatted .
train
false
15,136
def _Intersect(handler_list): if (not handler_list): return set() handlers = set([handler_list[0]]) for input_handler in handler_list[1:]: new_handlers = set() for g in handlers: new_handlers |= _IntersectTwoHandlers(input_handler, g) handlers = new_handlers return list(handlers)
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returns an unordered list of all possible intersections of handlers .
train
false
15,139
def test_Gpujoin_inplace(): s = T.lscalar() data = numpy.array([3, 4, 5], dtype=theano.config.floatX) x = gpuarray_shared_constructor(data, borrow=True) z = T.zeros((s,)) join = GpuJoin(view=0) c = join(0, x, z) f = theano.function([s], theano.Out(c, borrow=True)) assert (x.get_value(borrow=True, return_internal_type=True) is f(0)) assert numpy.allclose(f(0), [3, 4, 5])
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test gpujoin to work inplace .
train
false
15,140
def restarted(manager, containers, count, name): containers.refresh() for container in manager.get_differing_containers(): manager.stop_containers([container]) manager.remove_containers([container]) containers.refresh() manager.restart_containers(containers.running) started(manager, containers, count, name)
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require a service to be restarted .
train
false
15,142
def ParseJSONResponse(response): content_type = response.headers.get('Content-Type', '') if (not any((content_type.startswith(x) for x in _CONTENT_TYPES))): raise web.HTTPError(response.code, ('%r' % response.headers)) try: json_dict = json.loads(response.body) except: if (response.code == 200): raise json_dict = {'error': response.body} if (response.code != 200): error = 'unknown' if (isinstance(json_dict, dict) and json_dict.get('error')): error = json_dict.get('error') raise web.HTTPError(response.code, ('%s' % error)) return json_dict
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parse the json-encoded contents of the response body and return the python data object .
train
false
15,143
def hough_ellipse(img, threshold=4, accuracy=1, min_size=4, max_size=None): return _hough_ellipse(img, threshold, accuracy, min_size, max_size)
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perform an elliptical hough transform .
train
false
15,144
@pytest.mark.cmd @pytest.mark.parametrize('command,app', [(command, app) for (command, app) in get_commands().iteritems() if (app.startswith('pootle_') or (app in CORE_APPS_WITH_COMMANDS))]) def test_initdb_help(capfd, command, app): print ('Command: %s, App: %s' % (command, app)) with pytest.raises(SystemExit): call_command(command, '--help') (out, err) = capfd.readouterr() assert ('--help' in out)
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catch any simple command issues .
train
false
15,146
def is_email_valid(email_address): return (invalid_email_reason(email_address, '') is None)
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determine if email is invalid .
train
false
15,148
def _username(): if pwd: username = pwd.getpwuid(os.getuid()).pw_name else: username = getpass.getuser() return username
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grain for the minion username .
train
true
15,150
def weights_bartlett(nlags): return (1 - (np.arange((nlags + 1)) / (nlags + 1.0)))
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bartlett weights for hac this will be moved to another module parameters nlags : int highest lag in the kernel window .
train
false
15,151
def init_flowgram_file(filename=None, n=0, l=400, prefix='/tmp/'): if (filename is None): (fd, filename) = mkstemp(dir=prefix, suffix='.dat') close(fd) fh = open(filename, 'w') fh.write(('%d %d\n' % (n, l))) return (fh, filename)
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opens a file in plain flowgram format and writes header information .
train
false
15,153
def adjust_timestamp(ts, offset, here=utcoffset): return (ts - ((offset - here()) * 3600))
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adjust timestamp based on provided utcoffset .
train
false
15,154
def do_organization_info(ava): if (ava is None): return None org = md.Organization() for (dkey, (ckey, klass)) in ORG_ATTR_TRANSL.items(): if (ckey not in ava): continue if isinstance(ava[ckey], basestring): setattr(org, dkey, [_localized_name(ava[ckey], klass)]) elif isinstance(ava[ckey], list): setattr(org, dkey, [_localized_name(n, klass) for n in ava[ckey]]) else: setattr(org, dkey, [_localized_name(ava[ckey], klass)]) return org
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description of an organization in the configuration is a dictionary of keys and values .
train
true
15,156
def compare_languge(language, lang_list): found = False for l in lang_list: if (language == l.lower()): found = True break return found
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check if language is found .
train
false
15,157
def rstrips(text, remove): return _strips('r', text, remove)
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removes the string remove from the right of text .
train
false
15,158
def send_nscript(title, msg, gtype, force=False, test=None): if test: script = test.get('nscript_script') parameters = test.get('nscript_parameters') else: script = sabnzbd.cfg.nscript_script() parameters = sabnzbd.cfg.nscript_parameters() if (not script): return T('Cannot send, missing required data') title = (u'SABnzbd: ' + Tx(NOTIFICATION.get(gtype, 'other'))) if (force or check_classes(gtype, 'nscript')): script_path = make_script_path(script) if script_path: (output, ret) = external_script(script_path, gtype, title, msg, parameters) if ret: logging.error((T('Script returned exit code %s and output "%s"') % (ret, output))) return (T('Script returned exit code %s and output "%s"') % (ret, output)) else: logging.info(('Successfully executed notification script ' + script_path)) else: return (T('Notification script "%s" does not exist') % script_path) return ''
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run users notification script .
train
false
15,159
def lint_repeats(tool_xml, lint_ctx): repeats = tool_xml.findall('./inputs//repeat') for repeat in repeats: if ('name' not in repeat.attrib): lint_ctx.error('Repeat does not specify name attribute.') if ('title' not in repeat.attrib): lint_ctx.error('Repeat does not specify title attribute.')
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lint repeat blocks in tool inputs .
train
false
15,160
def _iscommand(cmd): if _isexecutable(cmd): return True path = os.environ.get('PATH') if (not path): return False for d in path.split(os.pathsep): exe = os.path.join(d, cmd) if _isexecutable(exe): return True return False
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return true if cmd is executable or can be found on the executable search path .
train
false
15,161
def test_cache_deactivated_remove_data(config_stub, tmpdir): config_stub.data = {'storage': {'cache-size': 1024}, 'general': {'private-browsing': True}} disk_cache = cache.DiskCache(str(tmpdir)) url = QUrl('http://www.example.com/') assert (not disk_cache.remove(url))
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test removing some data from a deactivated cache .
train
false
15,163
def describe_template_sets(): import inspect import sys templatesets = inspect.getmembers(sys.modules[__name__], inspect.isfunction) for (name, obj) in templatesets: if (name == 'describe_template_sets'): continue print(name, obj.__doc__, '\n')
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print the available template sets in this demo .
train
false
15,164
def _load_all_namespaces(resolver): url_patterns = getattr(resolver, 'url_patterns', []) namespaces = [url.namespace for url in url_patterns if (getattr(url, 'namespace', None) is not None)] for pattern in url_patterns: namespaces.extend(_load_all_namespaces(pattern)) return namespaces
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recursively load all namespaces from url patterns .
train
false
15,165
def get_provider_driver_class(driver, namespace=SERVICE_PROVIDERS): try: driver_manager = stevedore.driver.DriverManager(namespace, driver).driver except ImportError: return driver except RuntimeError: return driver new_driver = ('%s.%s' % (driver_manager.__module__, driver_manager.__name__)) LOG.warning(_LW('The configured driver %(driver)s has been moved, automatically using %(new_driver)s instead. Please update your config files, as this automatic fixup will be removed in a future release.'), {'driver': driver, 'new_driver': new_driver}) return new_driver
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return path to provider driver class in order to keep backward compatibility with configs < kilo .
train
false
15,166
def list_refs(refnames=None, repo_dir=None, limit_to_heads=False, limit_to_tags=False): argv = ['git', 'show-ref'] if limit_to_heads: argv.append('--heads') if limit_to_tags: argv.append('--tags') argv.append('--') if refnames: argv += refnames p = subprocess.Popen(argv, preexec_fn=_gitenv(repo_dir), stdout=subprocess.PIPE) out = p.stdout.read().strip() rv = p.wait() if rv: assert (not out) if out: for d in out.split('\n'): (sha, name) = d.split(' ', 1) (yield (name, sha.decode('hex')))
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yield tuples for all repository refs unless refnames are specified .
train
false
15,167
def _ts_kde(ax, x, data, color, **kwargs): kde_data = [] (y_min, y_max) = (data.min(), data.max()) y_vals = np.linspace(y_min, y_max, 100) upsampler = interpolate.interp1d(x, data) data_upsample = upsampler(np.linspace(x.min(), x.max(), 100)) for pt_data in data_upsample.T: pt_kde = stats.kde.gaussian_kde(pt_data) kde_data.append(pt_kde(y_vals)) kde_data = np.transpose(kde_data) rgb = mpl.colors.ColorConverter().to_rgb(color) img = np.zeros((kde_data.shape[0], kde_data.shape[1], 4)) img[:, :, :3] = rgb kde_data /= kde_data.max(axis=0) kde_data[(kde_data > 1)] = 1 img[:, :, 3] = kde_data ax.imshow(img, interpolation='spline16', zorder=2, extent=(x.min(), x.max(), y_min, y_max), aspect='auto', origin='lower')
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upsample over time and plot a kde of the bootstrap distribution .
train
false
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def status_battery(): data = status() if ('TONBATT' in data): return (not (data['TONBATT'] == '0 Seconds')) return {'Error': 'Battery status not available.'}
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return true if running on battery power cli example: .
train
false
15,171
def set_gamedir(path): global GAMEDIR Ndepth = 10 settings_path = os.path.join('server', 'conf', 'settings.py') for i in range(Ndepth): gpath = os.getcwd() if ('server' in os.listdir(gpath)): if os.path.isfile(settings_path): GAMEDIR = gpath return os.chdir(os.pardir) print(ERROR_NO_GAMEDIR) sys.exit()
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set gamedir based on path .
train
false
15,172
def SetQuickFixList(quickfix_list, focus=False, autoclose=False): vim.eval(u'setqflist( {0} )'.format(json.dumps(quickfix_list))) OpenQuickFixList(focus, autoclose)
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populate the quickfix list and open it .
train
false
15,174
def downsample(data, n, axis=0, xvals='subsample'): ma = None if (hasattr(data, 'implements') and data.implements('MetaArray')): ma = data data = data.view(np.ndarray) if hasattr(axis, '__len__'): if (not hasattr(n, '__len__')): n = ([n] * len(axis)) for i in range(len(axis)): data = downsample(data, n[i], axis[i]) return data if (n <= 1): return data nPts = int((data.shape[axis] / n)) s = list(data.shape) s[axis] = nPts s.insert((axis + 1), n) sl = ([slice(None)] * data.ndim) sl[axis] = slice(0, (nPts * n)) d1 = data[tuple(sl)] d1.shape = tuple(s) d2 = d1.mean((axis + 1)) if (ma is None): return d2 else: info = ma.infoCopy() if ('values' in info[axis]): if (xvals == 'subsample'): info[axis]['values'] = info[axis]['values'][::n][:nPts] elif (xvals == 'downsample'): info[axis]['values'] = downsample(info[axis]['values'], n) return MetaArray(d2, info=info)
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downsample by averaging points together across axis .
train
false
15,175
def config_edit_using_option_strings(config_filepath, desired_option_strings, section, edit=False): desired_options = [parse_option_string(section, desired_option_string, raise_on_error=True) for desired_option_string in desired_option_strings] config_edit(config_filepath, desired_options, edit=edit)
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writes the desired_option_strings to the config file .
train
false